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Published on: March 5, 2018
Molecular diagnosis of minimal residual disease in head and neck cancer patients
A Peggy Graveland1, Boudewijn J M Braakhuis, Simone E J Eerenstein
1Department of Otolaryngology/Head and Neck Surgery, VU University Medical Center, PO Box 7057, 1007 MB, Amsterdam, The Netherlands.
Aim:
Locoregional recurrences and distant metastases in adequately treated head and neck squamous cell carcinoma (HNSCC) patients have a dismal effect on survival. Tumor cells that escape histopathological detection might be the prime cause of this effect. We evaluated whether minimal residual cancer (MRC) in deep surgical margins and disseminated tumor cells (DTCs) in bone marrow aspirates are associated with clinicohistopathological parameters and outcome.
Methods:
Submucosal samples of deep resection margins of 105 HNSCC patients with histopathologically tumor-free surgical margins were analysed for the presence of MRC using hLy-6D qRT-PCR. Bone-marrow aspirates of 76 of these patients were analysed for DTCs by immunocytochemical staining. Presence of molecular-positive deep surgical margins, presence of DTC in bone marrow aspirates, and clinicohistopathological parameters were tested for associations with survival parameters by univariate and multivariate analyses.
Results:
In addition to lymph node stage, it appeared that vasoinvasive growth and particularly infiltrative growth pattern are significant predictors for locoregional recurrence (p = 0.041 and p = 0.006, respectively) and disease-free survival (p = 0.014 and p = 0.008, respectively). Remarkably, neither the presence of molecular-positive deep surgical margins nor that of DTC in bone marrow aspirates were significantly related to outcome.
Conclusions:
The presence of vasoinvasive and infiltrative growth in HNSCC tumor specimens are significant risk-factors for locoregional recurrence and disease-free survival. At present there seems no role for molecular analysis of deep surgical margins and bone marrow aspirates in predicting outcome with the methods used.
Insights
Minimal residual cancer (MRC) and disseminated tumor cells (DTCs) in head and neck squamous cell carcinoma (HNSCC) patients did not predict outcomes. Vasoinvasive and infiltrative growth patterns are significant predictors of recurrence and survival in HNSCC.
Area of Science:
- Oncology
- Surgical Pathology
- Molecular Diagnostics
Background:
- Locoregional recurrences and distant metastases significantly impact survival in head and neck squamous cell carcinoma (HNSCC) patients.
- Tumor cells evading histopathological detection are suspected to drive these adverse outcomes.
- Assessing minimal residual cancer (MRC) and disseminated tumor cells (DTCs) may offer prognostic insights.
Purpose of the Study:
- To evaluate the association between MRC in deep surgical margins, DTCs in bone marrow aspirates, and clinicohistopathological parameters in HNSCC patients.
- To determine if MRC and DTCs correlate with patient outcomes, specifically recurrence and survival.
Main Methods:
- Analysis of submucosal deep resection margins from 105 HNSCC patients for MRC using hLy-6D qRT-PCR.
- Analysis of bone marrow aspirates from 76 patients for DTCs via immunocytochemical staining.
- Univariate and multivariate analyses to correlate molecular findings and clinicohistopathological parameters with survival outcomes.
Main Results:
- Vasoinvasive growth (p = 0.041) and infiltrative growth patterns (p = 0.006) were significant predictors of locoregional recurrence.
- These growth patterns also significantly predicted disease-free survival (p = 0.014 and p = 0.008, respectively).
- Neither molecular-positive deep surgical margins nor the presence of DTCs in bone marrow were significantly associated with patient outcomes.
Conclusions:
- Vasoinvasive and infiltrative growth patterns in HNSCC tumor specimens are significant risk factors for locoregional recurrence and reduced disease-free survival.
- Current molecular methods for analyzing deep surgical margins and bone marrow aspirates do not appear to have a role in predicting HNSCC outcomes.
